Plot: Sheriff Owens is a man who has resigned himself to a life of fighting what little crime takes place in sleepy border town Sommerton Junction after leaving his LAPD post following a bungled operation that left him wracked with failure and defeat after his partner was crippled. After a spectacular escape from an FBI prisoner convoy, the most notorious, wanted drug kingpin in the hemisphere is hurtling toward the border at 200 mph in a specially outfitted car with a hostage and a fierce army of gang members. He is headed, it turns out, straight for Summerton Junction, where the whole of U.S. law enforcement will have their last opportunity to make a stand and intercept him before he slips across the border forever. At first reluctant to become involved, and then counted out because of the perceived ineptitude of his small town force, Owens ultimately accepts responsibility for the face off.

Description: After the death of their grandfather Johann von Wolfhause, the brothers Jan and Todd Wolfhouse travel to Munich to fulfill a family tradition, spreading the ashes of Johann during the Oktoberfest. Their contact brings them to a secret beer competition, the Beerfest", where they are offended by Baron Wolfgang von Wolfhausen and the German branch of their family that accuse their great-grandmother of being a prostitute and their grandfather of stealing an old recipe of the best beer in Germany. Jan and Todd returns to USA humiliated and decide to organize a beer team to dispute the next Beerfest. They join Landfill, Barry and Fink and train long the year to participate in the competition. When they find the lost recipe hidden in a dummy, they feel that their German relatives told the truth. But the team is ready for the tough dispute.

Making Java Groovy is a practical handbook for developers who want to blend Groovy into their day-to-day work with Java. It starts by introducing the key differences between Java and Groovy-and how you can use them to your advantage. Then, it guides you step-by-step through realistic development challenges, from web applications to web services to desktop applications, and shows how Groovy makes them easier to put into production.

Machine learning, at its core, is concerned with transforming data into actionable knowledge. This fact makes machine learning well-suited to the present-day era of "big data" and "data science". Given the growing prominence of R-a cross-platform, zero-cost statistical programming environment-there has never been a better time to start applying machine learning. Whether you are new to data science or a veteran, machine learning with R offers a powerful set of methods for quickly and easily gaining insight from your data.